Download e-book for iPad: Advances in Visual Data Compression and Communication: by Feng Wu

By Feng Wu

ISBN-10: 1439850461

ISBN-13: 9781439850466

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Visible info is likely one of the richest and so much bandwidth-consuming modes of communique. to satisfy the necessities of rising purposes, strong facts compression and transmission ideas are required to accomplish hugely effective verbal exchange, even within the presence of turning out to be communique channels that supply elevated bandwidth.Presenting the result of the author's years of study on visible data Read more...

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Extra info for Advances in Visual Data Compression and Communication: Meeting the Requirements of New Applications

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If F(s) is continuous, the random variable is said to be continuous. Let f (s) = F (s) when the derivative exists. If ∞ −∞ f (s) = 1, f (s) is called the probability density function (PDF) for S. The set where f (s) > 0 is called the support set of S. 13) Ω where Ω is the support set of the random variable. √ 2 2 If S is a zero-mean Gaussian variable, that is, S ∼ f (s) = (1/ 2πσ 2 ) × e−s /2σ , h(S) = − =− f (s) ln f (s)ds, f (s) − √ s2 − ln 2πσ 2 ds, 2σ 2 ES2 1 + ln 2πσ 2 , 2σ 2 2 1 1 = + ln 2πσ 2 , 2 2 1 1 = ln e + ln 2πσ 2 , 2 2 1 = ln 2πeσ 2 .

An index set {1, 2, · · · , M}. 2. An encoding function Y n : {1, 2, · · · , M} → Y n , yielding codewords Y n (1), Y n (2), · · · , Y n (M). The set of codewords is called the codebook. 3. A decoding function g : Yˆ n → {1, 2, · · · , M}, which is a deterministic rule to assign a guess to each possible received vector. 55) yˆn be the conditional probability of error given that index i was sent, where I() is the indicator function. The maximal probability of error λ (n) for an (M, n) code is defined as λ (n) = max λi .

3. All rates below capacity C are achievable. Specifically, for every rate R < C, there exists a sequence of (2nR , n) codes with maximum probability of error λ (n) → 0. Conversely, any sequence of (2nR , n) codes with λ (n) → 0 must have R ≤ C. 1 proved by Cover and Thomas [5]. The channel coding theorem promises the existence of block codes that will allow us to transmit information at rates below capacity with an arbitrarily small probability of error if the block length is large enough. In this chapter, we will not discuss the capacity-achieving channel codes.

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Advances in Visual Data Compression and Communication: Meeting the Requirements of New Applications by Feng Wu


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